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stevhliu
updated
a
dataset
about 10 hours ago
Post
619
If you're using any HF libraries, you should enable the Hub MCP in your agentic coding tool!
The brand new Docs Semantic Search tool is intravenous caffeine supply for Cursor, enables to correct API errors in a few seconds, gj @mishig ⚡️⚡️
👉 To enable Hub MCP, head to your account setting, under MCP, and it will give you everything you need!
The brand new Docs Semantic Search tool is intravenous caffeine supply for Cursor, enables to correct API errors in a few seconds, gj @mishig ⚡️⚡️
👉 To enable Hub MCP, head to your account setting, under MCP, and it will give you everything you need!
Upload calibration gui images
#516 opened about 18 hours ago
by
aliberts
arthurbresnu
posted
an
update
1 day ago
Post
1340
‼️Sentence Transformers v5.0 is out! The biggest update yet introduces Sparse Embedding models, encode methods improvements, Router module & much more. Sparse + Dense = 🔥 hybrid search performance!
1️⃣ Sparse Encoder Models - New support for sparse embeddings (30k+ dims, <1% non-zero)
* Full SPLADE, Inference-free SPLADE, CSR support
* 4 new modules, 12 losses, 9 evaluators
* Integration with elastic, opensearch-project, Qdrant, ibm-granite
* Decode interpretable embeddings
* Hybrid search integration
2️⃣ Enhanced Encode Methods
* encode_query & encode_document with auto prompts
* Direct device list passing to encode()
* Cleaner multi-processing
3️⃣ Router Module & Training
* Different paths for queries vs documents
* Custom learning rates per parameter group
* Composite loss logging
* Perfect for two-tower architectures
4️⃣ Documentation & Training
* New Training/Loss Overview docs
* 6 training example pages
* Search engine integration examples
Read the comprehensive blogpost about training sparse embedding models: https://huggingface.co/blog/train-sparse-encoder
See the full release notes here: https://github.com/UKPLab/sentence-transformers/releases/v5.0.0
What's next? We would love to hear from the community! What sparse encoder models would you like to see? And what new capabilities should Sentence Transformers handle - multimodal embeddings, late interaction models, or something else? Your feedback shapes our roadmap!
I'm incredibly excited to see the community explore sparse embeddings and hybrid search! The interpretability alone makes this a game-changer for understanding what your models are actually doing.
🙏 Thanks to @tomaarsen for this incredible opportunity!
1️⃣ Sparse Encoder Models - New support for sparse embeddings (30k+ dims, <1% non-zero)
* Full SPLADE, Inference-free SPLADE, CSR support
* 4 new modules, 12 losses, 9 evaluators
* Integration with elastic, opensearch-project, Qdrant, ibm-granite
* Decode interpretable embeddings
* Hybrid search integration
2️⃣ Enhanced Encode Methods
* encode_query & encode_document with auto prompts
* Direct device list passing to encode()
* Cleaner multi-processing
3️⃣ Router Module & Training
* Different paths for queries vs documents
* Custom learning rates per parameter group
* Composite loss logging
* Perfect for two-tower architectures
4️⃣ Documentation & Training
* New Training/Loss Overview docs
* 6 training example pages
* Search engine integration examples
Read the comprehensive blogpost about training sparse embedding models: https://huggingface.co/blog/train-sparse-encoder
See the full release notes here: https://github.com/UKPLab/sentence-transformers/releases/v5.0.0
What's next? We would love to hear from the community! What sparse encoder models would you like to see? And what new capabilities should Sentence Transformers handle - multimodal embeddings, late interaction models, or something else? Your feedback shapes our roadmap!
I'm incredibly excited to see the community explore sparse embeddings and hybrid search! The interpretability alone makes this a game-changer for understanding what your models are actually doing.
🙏 Thanks to @tomaarsen for this incredible opportunity!
Post
1521
In case you missed it, Hugging Face expanded its collaboration with Azure a few weeks ago with a curated catalog of 10,000 models, accessible from Azure AI Foundry and Azure ML!
@alvarobartt cooked during these last days to prepare the one and only documentation you need, if you wanted to deploy Hugging Face models on Azure. It comes with an FAQ, great guides and examples on how to deploy VLMs, LLMs, smolagents and more to come very soon.
We need your feedback: come help us and let us know what else you want to see, which model we should add to the collection, which model task we should prioritize adding, what else we should build a tutorial for. You’re just an issue away on our GitHub repo!
https://huggingface.co/docs/microsoft-azure/index
@alvarobartt cooked during these last days to prepare the one and only documentation you need, if you wanted to deploy Hugging Face models on Azure. It comes with an FAQ, great guides and examples on how to deploy VLMs, LLMs, smolagents and more to come very soon.
We need your feedback: come help us and let us know what else you want to see, which model we should add to the collection, which model task we should prioritize adding, what else we should build a tutorial for. You’re just an issue away on our GitHub repo!
https://huggingface.co/docs/microsoft-azure/index
sergiopaniego
posted
an
update
3 days ago
Post
906
📣 CALL FOR CONTRIBUTORS! 📣
Following last week’s full release of Gemma 3n, we launched a dedicated recipes repo to explore and share use cases. We already added some! 🧑🍳
Now we’re inviting the community to contribute and showcase how these models shine! ✨
Let them cook.
Check it out: https://github.com/huggingface/huggingface-gemma-recipes/issues/4
Following last week’s full release of Gemma 3n, we launched a dedicated recipes repo to explore and share use cases. We already added some! 🧑🍳
Now we’re inviting the community to contribute and showcase how these models shine! ✨
Let them cook.
Check it out: https://github.com/huggingface/huggingface-gemma-recipes/issues/4
- 1 reply
Post
2731
As you might have already heard, FLUX.1-Kontext-dev is now released and taken the generative community by storm!
In case you haven't come across it, you can get started with Kontext using 🤗 diffusers. See the official [model]( black-forest-labs/FLUX.1-Kontext-dev) and [docs](https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux#flux).
Want to know how inference companies like Fal & Replicate are able to run the model so fast and in under 2 seconds per image? Check out this [gist](https://gist.github.com/a-r-r-o-w/d08c37e8bd3e9c26b4ce80360be148c6) for some details!
In case you haven't come across it, you can get started with Kontext using 🤗 diffusers. See the official [model]( black-forest-labs/FLUX.1-Kontext-dev) and [docs](https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux#flux).
Want to know how inference companies like Fal & Replicate are able to run the model so fast and in under 2 seconds per image? Check out this [gist](https://gist.github.com/a-r-r-o-w/d08c37e8bd3e9c26b4ce80360be148c6) for some details!
- 1 reply
thomwolf
authored
a
paper
6 days ago
guipenedo
authored
a
paper
6 days ago
EmilyWitko
posted
an
update
6 days ago
Post
1887
Enjoy seven seconds on what I have to say about companies that have hiring quotas and zero other plans to support underrepresented staff:
freddyaboulton
posted
an
update
8 days ago
Post
262
Just published: Nano-vLLM meets Inference Endpoints
I show how to bind Nano-vLLM (supporting Qwen3-0.6B) to a web service — and deploy it easily on Hugging Face Inference Endpoints.
Minimalist engine, maximum fun!
https://huggingface.co/blog/angt/nano-vllm-meets-inference-endpoints
I show how to bind Nano-vLLM (supporting Qwen3-0.6B) to a web service — and deploy it easily on Hugging Face Inference Endpoints.
Minimalist engine, maximum fun!
https://huggingface.co/blog/angt/nano-vllm-meets-inference-endpoints
Post
3151
Hackathons in Paris on July 5th and 6th!
Hugging Face just wrapped 4 months of deep work with AMD to push kernel-level optimization on their MI300X GPUs. Now, it's time to share everything we learned.
Join us in Paris at STATION F for a hands-on weekend of workshops and a hackathon focused on making open-source LLMs faster and more efficient on AMD.
Prizes, amazing host speakers, ... if you want more details, navigate to https://lu.ma/fmvdjmur!
Hugging Face just wrapped 4 months of deep work with AMD to push kernel-level optimization on their MI300X GPUs. Now, it's time to share everything we learned.
Join us in Paris at STATION F for a hands-on weekend of workshops and a hackathon focused on making open-source LLMs faster and more efficient on AMD.
Prizes, amazing host speakers, ... if you want more details, navigate to https://lu.ma/fmvdjmur!
- 2 replies
Post
2470
Huge new bio datasets just dropped!!!
Check out them out @
ginkgo-datapoints
Read the blog for more info: https://huggingface.co/blog/cgeorgiaw/gdp
Check out them out @
ginkgo-datapoints
Read the blog for more info: https://huggingface.co/blog/cgeorgiaw/gdp
cfahlgren1
posted
an
update
9 days ago
Post
257
I ran the Anthropic Misalignment Framework for a few top models and added it to a dataset:
cfahlgren1/anthropic-agentic-misalignment-results
You can read the reasoning traces of the models trying to blackmail the user and perform other actions. It's very interesting!!
You can read the reasoning traces of the models trying to blackmail the user and perform other actions. It's very interesting!!
sergiopaniego
posted
an
update
10 days ago
Post
406
One of my favorite perks of the Hugging Face Pro plan: ✨Dev mode✨
Connect your HF Space to VS Code and just build — with hot reload out of the box.
Game changer for fast prototyping. 💻
Google Colab made AI accessible. Now HF Spaces are doing it too! 😍
💡 New Hugging Face pricing: http://hf.co/pricing
💡 More details: https://huggingface.co/learn/cookbook/en/enterprise_cookbook_dev_spaces
Connect your HF Space to VS Code and just build — with hot reload out of the box.
Game changer for fast prototyping. 💻
Google Colab made AI accessible. Now HF Spaces are doing it too! 😍
💡 New Hugging Face pricing: http://hf.co/pricing
💡 More details: https://huggingface.co/learn/cookbook/en/enterprise_cookbook_dev_spaces
Post
1875
🗣️ Whose voice do we hear when AI speaks?
Every language carries its own cultural values and worldviews. So, when we build AI systems, we're not just deciding how they speak but also whose perspectives they represent.
Even choosing which dialect to train on in Norway becomes a question of inclusion and power. In Kenya, will AI speak Swahili from Nairobi or coastal regions? What about indigenous languages with rich oral traditions but limited written text, like Quechua in Peru or Cherokee in North America?
The path forward? Building WITH communities, not just FOR them. Working with local partners (libraries, universities, civil society), testing for cultural alignment, and asking hard questions about representation.
Just published some thoughts on this after my keynote in Norway a few weeks ago: https://huggingface.co/blog/giadap/when-ai-speaks
Every language carries its own cultural values and worldviews. So, when we build AI systems, we're not just deciding how they speak but also whose perspectives they represent.
Even choosing which dialect to train on in Norway becomes a question of inclusion and power. In Kenya, will AI speak Swahili from Nairobi or coastal regions? What about indigenous languages with rich oral traditions but limited written text, like Quechua in Peru or Cherokee in North America?
The path forward? Building WITH communities, not just FOR them. Working with local partners (libraries, universities, civil society), testing for cultural alignment, and asking hard questions about representation.
Just published some thoughts on this after my keynote in Norway a few weeks ago: https://huggingface.co/blog/giadap/when-ai-speaks
-
- 1 reply
Post
750
Now you can make Flux.1 your own within just 10GBs of VRAM. In our new blog post we walk you through the process step by step.
Check it out here: https://huggingface.co/blog/flux-qlora
Check it out here: https://huggingface.co/blog/flux-qlora
multimodalart
posted
an
update
14 days ago
Post
4914
Self-Forcing - a real-time video distilled model from Wan 2.1 by
@adobe
is out, and they open sourced it 🐐
I've built a live real time demo on Spaces 📹💨
multimodalart/self-forcing
I've built a live real time demo on Spaces 📹💨
multimodalart/self-forcing
-
- 3 replies
Post
2384
Webinar Alert
Build your first chatbot with a Hugging Face Spaces frontend and Gaudi-powered backend with @bconsolvo ! He will teach you how to build an LLM-powered chatbot using Streamlit and Hugging Face Spaces—integrating a model endpoint hosted on an Intel® Gaudi® accelerator.
Beginners are welcome
https://web.cvent.com/event/70e11f23-7c52-4994-a918-96fa9d5e935f/summary
Build your first chatbot with a Hugging Face Spaces frontend and Gaudi-powered backend with @bconsolvo ! He will teach you how to build an LLM-powered chatbot using Streamlit and Hugging Face Spaces—integrating a model endpoint hosted on an Intel® Gaudi® accelerator.
Beginners are welcome
https://web.cvent.com/event/70e11f23-7c52-4994-a918-96fa9d5e935f/summary
- 1 reply